Bell curve and its implication

Bell curve is usually called the normal distribution and sometimes the Gaussian distribution.
It is, in fact, the most widespread manner in which data have been found to be distributed. When employed to describe the distribution of data, the bell curve describes how, when you make many observations, most of them fall around the mean, which is represented by the peak of the curve.

As a rule of thumb, any variation within the margin of error should be ignored.

For many polls a margin of error of more than 5 percent is considered unacceptable, yet in our everyday lives we make judgments based on far fewer data points than that. People don’t get to play 100 years of professional basketball, invest in 100 apartment buildings, or start 100 chocolate-chip-cookie companies. And so when we judge their success at those enterprises, we judge them on just a few data points.

When we observe a success or a failure, we are observing one data point, a sample from under the bell curve that represents the potentialities that previously existed. We cannot know whether our single observation represents the mean or an outlier, an event to bet on or a rare happening that is not likely to be reproduced. But at a minimum we ought to be aware that a sample point is just a sample point, and rather than accepting it simply as reality, we ought to see it in the context of the standard deviation or the spread of possibilities that produced it.

The normal distribution not only helps us understand such discrepancies, but also has enabled a myriad of statistical applications widely employed today in both science and commerce—for example, whenever a drug company assesses whether the results of a clinical trial are significant, a manufacturer assesses whether a sample of parts accurately reflects the proportion of those that are defective, or a marketer decides whether to act on the results of a research survey.

The normal distribution describes the manner in which many phenomena vary around a central value that represents their most probable outcome.

Full Disclaimer: I am not a financial planner. The views expressed in this post are all mine and they may or may not suit your needs. Please do you own due diligence. I do not make money on any of the products suggested in this post. 


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